Cytometry Part B Clinical Cytometry · 2019 · 72 citations · 16 references
Life SciencesCell BiologyImmunologyCellular ImmunologyClinical ImmunologyImmunotechnologyBioanalytical Method ValidationCell CharacterizationAssay ReproducibilityCleanupFlow Cytometric Immune PhenotypingFlow Cytometric ImmunophenotypingImmune Cell PhenotypingReproducibility AnalysisReproducibility AssessmentResearch Reproducibility
High-dimensional mass cytometry data potentially enable a comprehensive characterization of immune cells. In order to positively affect clinical trials and translational clinical research, this advanced technology needs to demonstrate a high reproducibility of results across multiple sites for both peripheral blood mononuclear cells (PBMC) and whole blood preparations. A dry 30-marker broad immunophenotyping panel and customized automated analysis software were recently engineered and are commercially available as the Fluidigm® Maxpar® Direct™ Immune Profiling Assay™. In this study, seven sites received whole blood and six sites received PBMC samples from single donors over a 2-week interval. Each site labeled replicate samples and acquired data on Helios™ instruments using an assay-specific acquisition template. All acquired sample files were then automatically analyzed by Maxpar Pathsetter™ software. A cleanup step eliminated debris, dead cells, aggregates, and normalization beads. The second step automatically enumerated 37 immune cell populations and performed label intensity assessments on all 30 markers. The inter-site reproducibility of the 37 quantified cell populations had consistent population frequencies, with an average %CV of 14.4% for whole blood and 17.7% for PBMC. The dry reagent coupled with automated data analysis is not only convenient but also provides a high degree of reproducibility within and among multiple test sites resulting in a comprehensive yet practical solution for deep immune phenotyping.
16
Laurens van der Maaten, Geoffrey E. Hinton · Journal of Machine Learning Research · 2008 · 35.7K citations
Accelerating t-SNE using tree-based algorithms
Laurens van der Maaten · 2014 · 2.4K citations
Philippe Métézeau · Research in Microbiology · 1998 · 1.3K citations